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(Circulation. 2007;115:2652-2659.)
© 2007 American Heart Association, Inc.
Pediatric Cardiology |
From the University of Texas School of Public Health, Houston (L.G.B.), and Department of Pediatrics, University of California at Davis Childrens Hospital, Sacramento (J.P.M.).
Correspondence to James P. Marcin, MD, MPH, Department of Pediatrics, Section of Critical Care Medicine, 2516 Stockton Blvd, Sacramento, CA 95817. E-mail jpmarcin{at}ucdavis.edu
Received December 5, 2006; accepted March 9, 2007.
Background Previous reports have found an inverse relationship between pediatric cardiac surgery case volume and in-hospital mortality. This association has been noted recently to be decreasing for coronary artery bypass grafting, possibly because of improved training programs, quality improvement activities, or other innovations to improve outcomes. It is unknown whether the volume-mortality association among pediatric cardiac surgery patients is decreasing similarly.
Methods and Results We used data from the state of Californias patient discharge data set from the years 19982003 to replicate 4 previous research studies of pediatric cardiac surgery volume and mortality. The total number of pediatric surgeries varied from 12 801 to 13 971 depending on the selection criteria applied. Using this larger and more contemporary data set, we found a weaker and less consistent volume-mortality relationship than had been reported previously. We also developed a new model, which incorporated elements of the old models, and found a statistically significant relationship with higher volume and lower mortality (odds ratio=0.86 per 100-patient increase in annual volume; 95% CI, 0.81 to 0.92). Post hoc analyses show that this relationship was related to the performance of the single largest-volume hospital.
Conclusions With the use of data from California, the volume-mortality relationship among pediatric cardiac surgery patients has changed since previous research, such that the old models no longer describe a clear or consistent association. With the use of a continuous definition of volume and an updated model, an association is observed but is dependent on highly leveraged covariate patterns found in the largest-volume hospital.
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